Shenhao Wang is a Postdoctoral Associate at MIT Urban Mobility Lab. His research interest is the interaction of machine learning, decision-making theories, and urban transportation applications. His dissertation focused on how to provide mutual insights between deep learning and classical choice modeling, with an emphasis on the interpretability of “black box” deep neural networks in their applications to travel behavior. He also worked on decision-making under uncertainty for the cases of autonomous vehicles by using prospect theory. He has side interests in transportation policies, such as car restriction policies in China. Shenhao Wang earned his Interdepartmental PhD in Computer and Urban Science from MIT. He holds BA in Economics from Peking University and BA in architecture from Tsinghua university, Master of Science in Transportation, and Master of City Planning from MIT.
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